L40S vs TITAN V

FP16 performance on the L40S reaches 362 TFLOPS, over 26 times the TITAN V's 13.8 TFLOPS, accelerating deep learning training where half-precision computations dominate. FP32 at 91 TFLOPS on the L40S also exceeds the TITAN V's 13.8 TFLOPS by more than sixfold, benefiting simulation and rendering tasks. This compute advantage translates to training large neural networks in hours rather than days on the older GPU.

The L40S's 864 GB/s memory bandwidth supports larger batch sizes in inference and training, reducing data loading bottlenecks compared to the TITAN V's 653 GB/s. With 48 GB VRAM versus 12 GB, the L40S processes models exceeding 10 billion parameters without swapping, ideal for modern LLMs. FP8 capability at 724 TFLOPS on the L40S further optimizes low-precision inference, unavailable on the TITAN V.

Power draw at 350W TDP for the L40S reflects its density, versus 250W on the TITAN V, but yields far higher throughput per watt in AI scenarios.

Select the L40S for AI training and inference on large language models, where 48 GB VRAM and 362 TFLOPS FP16 enable handling datasets that exceed the TITAN V's 12 GB limit. Cloud availability from $0.40 per hour makes it scalable for production workloads. Its PCIe 4.0 interconnect and 864 GB/s bandwidth support multi-GPU setups without memory constraints.

The L40S excels in fine-tuning and generative AI, leveraging FP8 at 724 TFLOPS for efficient deployment.

Choose the TITAN V for legacy Volta-optimized software or research prototypes where 12 GB HBM2 suffices and 250W TDP fits power-constrained desktops. It avoids cloud costs if owned outright, though no live rental offers exist. Lower FP32 at 13.8 TFLOPS suits basic scientific computing without needing Ada features.